LASSO[1]} is an L1-norm regularization method whereby regularization is based on the sum of the absolute values of the fitting coefficients, which has the effect of shrinking a subset of parameters to zero. In this case, the objective function \(F_\mathrm {obj}\)  (Equation REF ) is minimized with the following additional constraint:
\(F^{\mathrm {LASSO}}_\mathrm {obj} = F_{\mathrm {obj}} + 2\alpha \sum _{i=1}^{n_i} \left|c_i\right|.\) 
